Differences of prevalence and risk factors of diabetic retinopathy among rural and urban residents in South China

doi:10.21203/rs.3.rs-2751558/v1

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Research Article

Differences of prevalence and risk factors of diabetic retinopathy among rural and urban residents in South China

https://doi.org/10.21203/rs.3.rs-2751558/v1

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Objective

To determine the prevalence of diabetic retinopathy (DR) and associated risk factors among rural and urban people living with diabetes mellitus (PwDM ) in southern China.

Methods

This cross-sectional study informed all the 3,646 PwDM aged > = 18 years in 2019. All were registered at primary health centers in Qujiang district. A questionnaire was administered to collect information on demographic, socioeconomic, medical and lifestyle factors. Blood glucose, lipids and indices of renal function were measured. Presence of DR was determined by trained graders based on fundus photographs using criteria of the United Kingdom National Health Service (NHS) Diabetic Eye Screening (DES) Programme. Multiple logistic regression analyses were used to assess potential risk factors for presence of DR.

Results

The mean age of the 2,677 participants (73.4%) was 63.4 years (SD 10.1 years), 1,503 (56.2%) were female, 1,749 (65.3%) were rural residents, 1,654 (71.0%) participants had HbA1c > = 6.5%, 1,773 (66.3%) had uncontrolled high blood pressure, and the median duration of DM was < 5 years. Although half (52.0%) of these participants had brief (< 5 years) exposure to DM, 831 (31.3%, 95% CI: 29.3–32.8%) had DR, among whom 412 (49.6%) had sight threatening DR. Men (33.1%), had a significantly higher prevalence of any DR than women (29.4%, p < 0.05). There were no significant differences in DR prevalence at any level between rural and urban residents. In multivariate regression models, risk factors for any DR were HbA1C > 6.5% (OR = 1.58 p < 0.01), using insulin and hypoglycemic drugs (OR = 1.76, p < 0.01), longer duration of DM and higher systolic blood pressure (OR = 1.01 for each mmHg, p < 0.01).

Conclusion

Although half of participants had DM for < 5 years, the high prevalence of DR, poorly controlled blood glucose and uncontrolled hypertension highlight the need for better management of non-communicable diseases in rural China.

prevalence

risk factor

diabetic retinopathy

screening

rural

China

The global number of people with diabetes mellitus (PwDM) increased from 108 million in 1980 to 463 million in 2019, resulting in 4.2 million deaths that year^1–3. Diabetes mellitus (DM) and complications associated with the disease pose a significant burden on health systems globally. The average medical expenditure among PwDM was about 2.3 times higher than for those without DM, regardless of other medical conditions, in 2017 in the United States of America⁴. China has also observed a surge in DM prevalence among adults from < 1% in the 1980s to 10.9% in 2010^1,5.

Uncontrolled glucose levels among PwDM can damage blood vessels in the retina and lead to the development of diabetic retinopathy (DR). At the early stages of the disease, the damage is often asymptomatic, not affecting the central vision. This poses a significant danger to PwDM, as untreated DR can lead to vision impairment (VI) and eventual blindness (BL). However, early detection of DR via annual retinal examinations coupled with interventions such as laser retinal surgery, intraocular injection of anti-vascular endothelial growth factor (anti-VEGF), and/or vitrectomy surgery can reduce vision impairment by > 90%^6,7. DM also increases the risk of glaucoma, cataract and other ocular problems. Thus, access to screening through regular retinal imaging and effective referral for treatment are crucial to preventing vision loss among PwDM.

Among Chinese PwDM, prevalence of DR has been reported as 18.0% among urban dwellers in Eastern China during a community screening in 2015³, 18.5% from pooled prevalence of a review⁸, 27.9% from a multi-hospital-based study in 2015⁹, and 34% (95% CI:33.3–34.9) from a 6-province study in the same year¹⁰. Previous studies have established risk factors for DR, including longer duration of DM, higher levels of glycated haemoglobin (HbA1c %) and serum lipids, high blood pressure, living in rural areas and use of insulin^8,9.

Studies have reported that a large proportion of PwDM in China are undiagnosed^3,11. The prevalence of DR among diagnosed PwDM is between 18% and 34%^3,8−10. However, only half of those diagnosed with DM had ever received an eye examination.¹² China’s National Primary Health Care System recommends that PwDM register with township health units in rural areas, or community health centres in urban areas, for regular monitoring of their glucose levels and potential complications. However, most township health units and community health centres do not currently offer retinal examinations due to a national lack of trained technical staff.

In 2017, the “Integrated Diabetic Rural Eye Care” program, funded by the World Diabetes Foundation (WDF) and Orbis International, was launched. The program was a collaborative effort of the Provincial Health Commission and Zhongshan Ophthalmic Center, Sun Yat-sen University (a tertiary eye institute in Guangzhou, Southern China), and three prefectural and three county-level hospitals in Guangdong Province. The aim was to establish a model of Diabetic Retinopathy Screening (DRS) at the primary level in these areas.

Qujiang is a county-level district in Shaoguan Prefecture with a population of 305,500 and was included in the above program. The district has 10 towns, each with a township health unit to deliver chronic disease services, including DM management, to local residents. The WDF/Orbis DRS program in Qujiang District commenced in September 2019.

Relatively few studies on the prevalence of DR have been conducted in southern China, with most having been completed in China’s northern and eastern areas^8,13. One study undertaken in Guangdong Province in 2014, including only 562 participants, showed that the prevalence of DR among previously- and newly-diagnosed PwDM older than 50 years were 23.9% and 8.19%, respectively.¹¹ While population-based data are necessary to fully understand the nature of DM in rural China, including the percentage of persons diagnosed and under care, large studies of persons already receiving treatment for DM are also important to understand the current quality of care for PwDM. Few large studies such as those in Beijing^14–16, Suzhou³ have been done of this type in China, fewer still in rural medical facilities, and none assessing prevalence of DR using state of the art image assessment by trained graders. We conducted this study in Qujiang district on the prevalence and risk factors of DR among both rural and urban dwellers diagnosed with DM in order to inform policy makers and improve existing public health services.

Patient and public involvement statement:

Screening was announced through posters 1–2 months before in all villages. All PwDM registered in Qujiang (n = 3,646) were informed again by trained village doctors in the district of a scheduled DRS at the 10 township health units. Village doctors from 3 of the 10 towns were involved in the design of the questionnaires, which were pretested with and feedback from some PwDM. Participants were asked to let anyone they knew with diabetes in the area to come for the screening although they were not directly involved in recruitment and conducting of the study. They were informed of the medical examination results immediately on site or later via text, WeChat or mobile phone call.

Data Collection

Trained study team members at the screening sites included an ophthalmologist, two nurses, one technician, and three interviewers. Local general practitioners and nurses from each township health unit assisted with booking participants for screening, collecting basic information, drawing venous blood and coordinating site operations.

Participant information, including age, gender, body mass index (BMI), and history of smoking and alcohol consumption, duration of DM, had all been previously recorded and annually updated at health centres by the local general practitioners following national guidelines for the management of chronic diseases. These data were retrieved from the record system when participants arrived at the screening site. Screening began with assessment of each participant’s weight, height, and blood pressure. A health questionnaire was administered, including items on official place of residence (rural vs urban), marital status, type of medical insurance, level of education, methods for control of glucose, knowledge, attitudes and practices concerning DM, and participants’ assessment of the quality of screening services and their own health and economic situation. Participants were asked their currently used method(s) of glucose control: insulin, hypoglycemic drugs, diet and traditional Chinese medicine, exercise, and no treatment. After preliminary information was collected, venous blood was drawn from each consenting participant in order to assess HbA1C and kidney function prior to examination of their eyes. Hypertension was defined as presenting with systolic pressure > = 140 mmHg, diastolic pressure > = 90 mmHg, or having been previously diagnosed.

Finally, an ophthalmic examination was conducted as follows: A trained nurse tested presenting visual acuity (PVA) using an illuminated Snellen chart at 6 metres. An ophthalmologist examined the anterior segment under a slit lamp and tested intra-ocular pressure (IOP) using a hand-held tonometer (Tonopen, Reichert, USA). For participants with normal IOP and without narrow angles, assessed by using the Van Herrick method¹⁷, the ophthalmic nurse dilated pupils bilaterally with one to two drops of tropicamide (0.25%) 2–5 minutes before capturing images. Participants thought to be at risk of side effects from pharmacologic dilation, based on assessment of the anterior chamber angle, IOP > 21 mmHg (suggested by the local ophthalmologists) or a history of symptoms suggested of acute angle closure attack, were taken to a dark room for 3 to 5 minutes to undergo scotopic pupillary dilation instead. Two fundus images were captured from each dilated eye by a trained technician. For eyes with IOP < 21mmHg, one image was centered at the optic nerve head and the other at the macula. Fundus images were captured directly without dilation for those with IOP > = 21mmHg or who had been previously diagnosed with glaucoma, and those without reaction on scotopic pupillary dilation. If the technician was not satisfied with the first round of images taken, the process was repeated until the images were clear, unless the ophthalmologist at the screening site indicated the blurred image was due to media opacity, in which case further image capture in the eye was not attempted. All images were taken in a darkened room with a digital non-mydriatic fundus camera (Fundus Vue, Crystal Vue, Taipei, Taiwan) with a 45⁰ field of view.

Biochemical Detection

Venous blood collected from participants were sent to the local county hospital for the tests on bio-chemical indicators on the same day. Normal reference value for blood urea nitrogen (BUN) is 2.9–8.2 mmol/L and creatinine (Cr) is 62–115 umol/L.

Image Grading And Definition Of Visual Acuity:

Images were uploaded to ZOC’s online grading system (https://grader.com) and independently assessed by two certified graders, each with > 5 years of experience. Graders discussed the results and resolved any disagreements. The English National Screening Program Standard⁷ was followed to grade the quality of images (ungradable vs gradable) and the presence and severity of DR.

DR was graded as R0, R1, R2, R3a or R3s and diabetic macular oedema (DME) was graded as M0, and M1⁷. These are defined below: Grade R0: absence of any DR features including microaneurysm. Grade R1: microaneurysm(s) with or without exudates, but no other DR futures. Grade R2: any venous beading, cotton wool spots, venous reduplication, multiple blot hemorrhage, and/or intra-retinal microvascular abnormalities. Grade R3a: proliferative retinopathy, such as new blood vessels and/or hemorrhage within the retina or vitreous, or presence of traction. Grade R3s: the eye has received prior retinal laser treatment with stable DR features. Grade M0: no evidence of DME. Grade M1: microaneurysms, hemorrhage, or exudes that within 2-disc diameters of the centre of the fovea.

The severity of each participant's DR was determined based on the grade of their worse-affected eye. If gradable images were available for only one eye, the participant’s grade depended on that eye alone. Sight threatening DR (STDR) was defined as the presence of pre-proliferative DR (R2), proliferative DR (R3) and/or maculopathy (M1). If images were ungradable, the photographer at the screening site would record reasons for this in consultation with the ophthalmologist. These could include opacity of the cornea, anterior chamber, lens or vitreous. Ungradable eyes were included in the denominator when the prevalence of DR was computed in SPSS model in this article. Participants received screening report within 2 days by mobile phone text, Wechat with fundus images, or a hard copy from the health unit where fundus photos taken in a week for those did not leave mobile phone number.

Participants with visual impairment (VI) could be classified as blind (PVA < 3/60 in the better-seeing eye), severely visually impaired (SVI, PVA > = 3/60 but < 6/60), or moderately visually impaired (MVI) (PVA > = 6/60 but < 6/18). The cause(s) of vision impairment and blindness were also determined by the ophthalmologist on site upon the eye examination (DR or other ocular conditions) with torch, portable slit lamp, tono-pen and fundus camera. Should the eye have more than one co-morbidity, the most-easily treated condition was recorded as the cause of vision impairment.

Statistical Methods:

All analysis were performed using a commercially available statistical software package (SPSS for Windows, Version 26.0; SPSS, Chicago, IL). Prevalence of any DR, STDR, VI and blindness was calculated for all screening participants. Data were analyzed using person as the unit, with the exception of burden of VI/BL, which was calculated by person and by eye. Continuous variables were presented as means (standardized deviation, SD) or medians (interquartile range, IQR). Categorical variables were presented as frequencies and proportions. Duration of diagnosed diabetes and hypertension was stratified into intervals of 5 years. The Shapiro–Wilk normality test and histograms were used to evaluate the normality of continuous data. Univariate logistic regression was performed separately for potential predictors of any DR and STDR, and variables with a p-value < 0.2 were included in multi-variable logistic regression models.

Characteristics of participants:

Of the 3,646 PwDM contacted, 2,677 (73.4%) (1,503 [56.1%] female; mean age 63.4 years [SD 10.1, range 28–97 years]) participated in the screening (Fig. 1). Among participants, 346 (12.9%) refused to have their venous blood collected onsite, and fundus images for one person (0.04%) were not saved (Fig. 1). Most participants (n = 2,643, 98.7%) reported having Type-II DM, with 14 (0.5%) having type I, and 20 (0.7%) uncertain. Some half (1,392, 52.0%) of participants had been diagnosed with DM < 5 years ago, and for 229 (8.6%) the time since diagnosis was > = 15 years. Among participants attending the DRS, 473 (17.7%) had a history of smoking, 326 (12.2%) drank alcohol regularly, 333 (12.4%) had a family history of DM, and 1,654 (71.0%) had HbA1c > = 6.5%.

The mean age of PwDM who did not present for screening (65.2 [10.6] years) was significantly greater than for those who did ((63.4 [10.1] years, p < 0.01), and their mean systolic (130.6 [12.0] vs 137.0 [18.8], p < 0.01) and diastolic (79.2 [7.3] vs 82.1 [11.0], p < 0.01) blood pressures were significantly lower. There were no significant differences in mean BMI, gender, positive history of smoking or reported alcohol consumption between those who did and did not attend screening (Table 1).

Table 1

Characteristics of 3,646 people with diabetes mellitus who did and did not present for the screening in Qujiang District
	Total (n = 3,646)
Age (years)	63.9 (10.3)	63.4(10.1)	65.2(10.6)	< 0.01
Female sex	2037 (55.9%)	1503 (56.2%)	534(55.1%)	0.59
Positive history of smoking	662 (18.2%)	473(17,7%)	189(19.5%)	0.34
Self-reported regular use of alcohol	457 (12.5%)	326(12.2%)	131(13.5%)	0.37
Systolic blood pressure (mmHg)	135.3 (17.5)	137.0(18.8)	130.6(12.0)	< 0.01
Diastolic Blood pressure (mmHg)	81.4 (10.2)	82.1(11.0)	79.2(7.3)	< 0.01
Body mass index (kg/m2)	24.4 (4.9)	24.5(5.4)	24.3(3.2)	0.28

The proportions of people with moderate vision impairment (MVI), severe visual impairment (SVI) and blindness were 9.7% (n = 260), 0.7% (n = 18) and 1.0% (n = 27) respectively (Table 2). Only 329 (12.3%) participants had received a retinal examination in the previous year. Over half (1,773, 66.2%) of these PwDM had hypertension. Most participants (n = 2,147, 80.2%) were using insulin and/or hypoglycemic drugs, while the rest employed some combination of Chinese traditional medicines, diet or exercise. A total of 186 (6.9%) participants reported taking no measures to control their glucose (Table 2).

Table 2

Characteristics of participants to the diabetic retinopathy screening in Qujiang, stratified by official urban vs rural residence
Characteristic	Total (n = 2677)	Rural n = 1749 (65.3%)	Urban n = 928 (34.7%)	P value
Mean age (SD) Age (years) (categorized) < 50 50–59 60–69 >/=70 Female sex Self-reported history of smoking Self-reported regular use of alcohol Family history of DM High school and above education Mean HbA1c (%) (Standard Deviation - SD) HbA1C (%) > = 6.5* Mean blood urea nitrogen (BUN) (SD) (mmol/L) Mean creatinine (Cr) (SD) (µmol/L) Mean Body mass index (kg/m²) (SD) Visual acuity (better seeing eye) Moderate visual impairment Severe visual impairment Blindness Duration of DM < 5 years >=5 years, but less than 10 years >=10 years but less than 15 years >=15 years Mean systolic blood pressure (mmHg) Mean diastolic blood pressure (mmHg) Hypertension present Retinal examination in the previous year Use of insulin and/or hypoglycemic drugs	63.4 (10.1) 226 (8.4%) 704 (26.3%) 992 (37.1%) 755 (28.2%) 1503 (56.1%) 473 (17.7%) 326 (12.2%) 333 (12.4%) 322 (12.0%) 7.5 (1.6) 1654 (71.0%) 6.1 (2.2) 97.6 (44.6) 24.5 (5.4) 216 (8.1%) 18 (0.7%) 27 (1.0%) 1392 (52.0%) 716 (26.7%) 340 (12.7%) 229 (8.6%) 137.0 (18.8) 82.1 (11.0) 1773 (66.2%) 329 (12.3%) 2147 (80.2%)	62.4 (10.2) 174 (9.9%) 512 (29.3%) 636 (36.4%) 427 (24.4%) 985 (56.3%) 346 (73.1%) 234 (13.4%) 209 (11.9%) 142 (8.1%) 7.4 (1.6) 1061 (69.0%) 6.1 (2.3) 97.9 (41.2) 24.21(3.5) 146 (8.3%) 10 (0.6%) 21 (1.1%) 983 (56.2%) 469 (26.8%) 199 (11.4%) 98 (5.6%) 137.7 (18.9) 82.7 (11.1) 1144 (65.4%) 205 (11.7%) 1385 (79.2%)	65.3 (9.6) 52 (5.6%) 192 (20.7%) 356 (38.4%) 328 (35.3%) 518 (55.8%) 127 (26.9%) 92 (9.9%) 124 (13.4%) 180 (19.4%) 7.5 (1.5) 593 (74.8%) 6.1 (2.1) 97.1 (50.5) 24.36 (3.4) 70 (7.5%) 8 (0.9%) 6 (0.6%) 409 (44.1%) 247 (26.6%) 141 (15.2%) 131 (14.1%) 135.7 (18.4) 81.0 (10.7) 629 (67.8%) 124 (13.4%) 762 (82.1%)	< 0.01 < 0.01 0.80 < 0.01 < 0.01 0.29 < 0.01 0.10 < 0.01 0.64 0.70 0.30 0.47 0.38 0.21 < 0.01 < 0.01 0.91 < 0.01 < 0.01 0.01 < 0.01 0.22 0.22 0.07
BMI: Body mass index,
DM: diabetes mellitus, PVA: presenting visual acuity, SD: standard deviation. BP: blood pressure
Moderate visual impairment (MVI) presenting visual acuity (PVA>/=6/60, but < 6/18
Severe visual impairment (SVI) PVA>/=3/60, < 6/60
Blindness PVA < 3/60
*HbA1C (%) This value was missing for 346 (12.9%) of participants.

Over half of those screened (n = 1,745, 65.3%) were rural residents. There were no significant differences between rural and urban residents with regard to gender, family history of DM, prevalence of visual impairment and blindness, history of hypertension, body mass index (BMI), HbA1c or proportion who had received a retinal examination in the previous year, nor in their use of insulin and/or hypoglycemic drugs. However, rural dwellers were more likely to be smokers (p < 0.01), to drink alcohol regularly (p < 0.01), and to have been diagnosed with DM for < 5 years (p < 0.01). Among urban residents, a higher proportion had achieved an educational level of high school or above, had HbA1c (%) equal to or over 6.5 (p < 0.01), and had been diagnosed with DM for over 15 years (Table 2). The average age of urban residents [65.3 (SD 9.6) years] was significantly older than rural ones [62.4 (SD 10.2) (p < 0.01). Both mean systolic and diastolic blood pressures were significantly higher for rural residents (p < 0.05). (Table 2).

Prevalence Of Dr And Macular Edema:

Of the 2,676 people had fundus images taken, 20 (0.8%) had both eyes ungradable pictures taken. Nine of these 20 people had dense cataract, 1 had corneal opacity in his right eye and left eyeball absent, 1 had un-dilated too small pupil, and the other 9 had opacity at vitreous including asteroid hyalosis (3) or vitreous hemorrhage or fibrosis (6). Of the 5,352 eyes, there were another 168 (6.3%) unilateral eyes had ungradable images taken.

A total of 831 (31.1%, 95% CI: 29.3–32.8) participants had any DR. The prevalence of R1, R2, R3, M1 and STDR were 21.8% (95% CI: 20.3–23.4), 7.2% (95% CI: 6.2–8.2), 2.0% (95% CI: 1.5–2.6), 13.2% (95% CI: 11.9–14.4), and 15.4% (95%CI: 14.0–16.8) respectively. (Table 3). The prevalence of any DR, including STDR, was similar between rural and urban residents. The prevalence of both STDR (men: 17.5% vs women:13.7%, < 0.01) and any DR (men: 33.1% vs women: 29.4%, p < 0.05) were significantly higher in men. Participants with BMI of 18.5–24.9 (p < 0.01) demonstrated higher prevalence of DR compared to those with higher BMI. Longer duration of DM, having higher BUN and Cr were significantly associated with greater severity and higher prevalence of all levels of DR (p < 0.01).

Table 3

Prevalence of diabetic retinopathy in Qujiang among rural and urban residents and by age, sex and clinical status
DR grade	Any DR (n, %, 95% CI)	R3 (n, %, 95% CI)	M1 (n, %, 95% CI)	STDR# (n, %, 95% CI)
Total (n, %)	831(31.1%,29.3,32.8)	54(2.0%,1.5,2.6)	352(13.2%,11.9,14.4)	412(15.4%,14.0,16.8)
Residence
Rural(n = 1748,65.3%)	535(30.6%,28.4,32.8)	36(2.1%,1.4,2.7)	231(13.2%,11.6,14.8)	271(15.5%,13.8,17.2)
Urban(n = 928,34.7%)	296(31.9%,28.9,34.9)	18(1.9%,1.1,2.8)	121(13.0%,10.9,15.2)	141(15.2%,12.9,17.5)
P value	0.49	0.83	0.89	0.83
Age (years)
<50 (n = 218,8.1%)	73(32.3%,26.2,38.4)	6(2.7%,0.5,4.8)	32(14.2%,9.6,18.7)	40(17.7%,12.7,22.7)
50–59 (n = 779,29.1%)	258(36.6%,33.1,40.2)	18(2.6%,1.4,3.7)	123(17.5%,14.7,20.3)	140(19.9%,16.9,22.8)
60–69 (n = 899,33.6%)	310(31.3%,28.4,34.2)	19(1.9%,1.1,2.8)	127(12.8,10.7,14.9)	152(15.3%,13.1,17.6)
70- (n = 530,19.8%)	190(25.2%,22.1,28.3)	11(1.5%,0.6,2.3)	70(9.3%,7.2,11.3)	80(10.6%,8.4,12.8)
P value	< 0.01	0.43	< 0.01	< 0.01
Sex
Men (n = 1174,43.9%)	389(33.1%,30.4,35.8)	29(2.5%,1.6,3.4)	169(14.4%,12.4,16.4)	206(17.5%,15.4,19.7)
Women (n = 1502,56.1%)	442(29.4%,27.1,31.7)	25(1.7%,1.0,2.3)	183(12.2%,10.5,13.8)	206(13.7%,12.0,15.5)
P value	< 0.05	0.14	0.09	< 0.01
BMI (kg/m²)
BMI < 18.5	31(30.7%,21.5,39.8)	2(2.0%, 0.8,4.7)	12(11.9%,5.5,18.3)	15(14.9%,7.8,21.9)
BMI>/=18.5, but < 24.9	489(32.8%,30.4,35.2)	37(2.5%,1.7,3.3)	221(14.8%,13.0,16.6)	268(18.0%,16.0,19.9)
BMI>/=24.9 but < 30	269(28.7%,25.8,31.6)	11(1.2%,0.5,1.9)	100(10.7%,8.7,12.7)	109(11.6%,9.6,13.7)
BMI > = 30	42(28.8%,21.3,36.2)	4(2.7%,0.1,5.4)	19(19.2%,7.5,18.5)	20(13.7%,8.1,19.3)
P value	0.18	0.09	< 0.05	< 0.01
BUN (mmol/L) 715/2331)
< 2.9 2.9–8.2 > 8.2 P - value	12 (32.4%,16.6, 48.3) 593 (29.4%,27.4,31.4) 110 (39.9%,34.0,45.7) < 0.01	1 (2.7%, 0, 8.2) 27 (1.3%,0.8,1.8) 16 (5.8%,3.0,8.6) < 0.01	4 (10.8%,0.3,21.3) 244 (12.1%,11,13.9) 55 (19.9%,15.2,24.7) < 0.01	5 (13.5%,2.0,25.1) 284 (14.1%,12.6,15.6) 63 (22.8%,17.8,27.8) < 0.01
Creatinine (Cr) (µmol/L) <62 62–115 >115 P - value	13 (34.2%,18.4,50.0) 565 (29.0%,26.9,31.0) 137 (40.1%,34.8,45.3) < 0.01	2 (5.3%,0,12.7) 25 (1.3%,0.8,1.8) 17 (5.0%,2.7,7.3) < 0.01	6 (15.8%,3.6,27.9) 222 (11.4%,10.0,12.8) 75 (21.9%,17.5,26.3) < 0.01	6 (15.8%,3.6,27.9) 260 (13.3%,11.8,14.8) 86 (25.1%,20.5,29.8 < 0.01
Duration of DM (years)
<5	313(22.5%,20.3,24.7)	13(0.9%,0.4,1.4)	120(8.6%,7.1,10.1)	133(9.6%,8.0,11.1)
5–10	244(34.1%,30.6,37.6)	13(1.8%,0.8,2.8)	103(14.4%,11.7,17.0)	121(16.9%,14.1,19.7)
10–15	151(44.4%,39.1,49.7)	13(3.8%,1.8,5.9)	67(19.7%,15.5,24.0)	85(25.0%,20.4,29.6)
>=15	123(53.7%,47.2,60.2)	15(6.6%,3.3,9.8)	62(27.1%,21.3,32.9)	73(31.9%,25.8,38.0)
P value	< 0.01	< 0.01	< 0.01	< 0.01
Treatment
Insulin	139(47.9%,42.1,53.7)	11(3.8%,1.6,6.0)	68(23.4%,18.5,28.4)	88(30.3%,25,35.7)
Hypoglycemic drugs	582(31.4%,29.2,33.5)	37(2.0%1.4,2,6)	243(13.1%,11.6,14.6)	276 (14.9%,13.3,16.5)
No medication*	110(20.8%,17.3,24.2)	6(1.1%,0.2,2.0)	41(7.7%,5.5,10.0)	48(9.1%,6.6,11.5)
P value	< 0.01	< 0.05	< 0.01	< 0.01
Presence of hypertension
Present Absent	349(32.8%,30.0,35.7) 482(29.9%,27.6,32.1)	27(2.5%,1.6,3.5) 27(1.7%,1.0,2.3)	147(13.8%,11.8,15.9) 205(12.7%,11.1,14.3)	171(16.1%,13.9,18.3) 241(14.9%,13.2,16.7)
P value	0.11	0.12	0.40	0.44
# STDR: Sight threatening diabetic retinopathy
*This includes using Chinese Traditional Medicine, diet and exercises.

Having higher HbA1C (%), using insulin and/or hypoglycemic drugs, receiving a retinal examination in the previous year, having a longer duration of DM, higher BUN level, and having higher systolic blood pressure were independently associated with greater risk of any DR and of STDR (Table 4) in multivariate logistic regression models. PwDM older than 70 years were 45% less likely to have any DR and 29% less likely to have STDR (p < 0.01) (Table 4) than those younger than 50. Every one mmHg elevation in systolic blood pressure increased the risk of having any DR and STDR by 1.01 times (p < 0.01), and every 1% elevation in HbA1c increased the risk for any DR and STDR both by 1.26 times (p < 0.01).

Table 4: Risk factors for any diabetic retinopathy and sight-threatening diabetic retinopathy (STDR) among diabetic persons in Qujiang

Any DR

STDR

Factors

Univariate Analysis

Multivariate Regression

Univariate Analysis

Multivariate regression

OR (95%CI)

Sex

Female

Reference

Male

1.19(1.01,1.40) *

1.06 (0.88,1.29)

1.34(1.09,1.65) **

1.23 (0.96,1.56)

Age (years)

0.98 (0.97, 0.99) **

0.96 (0.96, 0.97) **

0.97 (0.96, 0.98) **

0.96 (0.94, 0.97) **

Residence

Urban

Reference

Rural

0.94(0.79,1.12)

1.02(0.82,1.28)

History of smoking

Absent

Reference

Present

1.22(0.99,1.51)

1.04(0.77,1.41)

1.26(0.97,1.63)

1.11(0.781,1.590)

Regular alcohol use

Absent

Reference

Present

1.21(0.94,1.54)

1.12(0.81,1.54)

1.10(0.81,1.51)

Family history of DM

Absent

Reference

Present

1.01(0.79,1.29)

1.36(1.02,1.83) *

1.14 (0.80,1.61)

Educational level

Below high school

Reference

High school or above

1.27(0.99,1.62) *

1.29 (0.97,1.72)

1.15(0.84,1.57)

Retinal examination in the last year

Absent

Reference

Present

1.51(1.19,1.92) **

1.28(0.95,1.64)

1.69(1.27,2.25) **

1.39 (1.00,1.93) *

Treatment of diabetes

No medication to control blood glucose

Reference

Using insulin and/or hypoglycemic drugs

2.43(1.92,3.08) **

1.80 (1.37, 2.37) **

2.65(1.88, 3.74) **

1.76 (1.20, 2.60) **

Duration of DM (years)

Reference

>=5, but <10

1.78(1.46,2.17) **

1.62 (1.30, 2.03) **

1.92(1.48,2.51) **

1.72 (1.27, 2.32) **

>=10 but <15

2.75(2.15,3.53) **

2.63 (1.97, 3.51) **

3.15(2.33,4.27) **

3.07 (2.15, 4.37) **

>=15

4.00(2.99,5.33) **

4.40 (3.14, 6.16) **

4.43(3.18,6.16) **

5.24 (3.54, 7.74) **

Blood Urea Nitrogen (BUN) (mmol/L)

1.09 (1.05, 1.13) **

1.05 (0.99, 1.11)

1.13 (1.08, 1.18) **

1.10 (1.02, 1.18) *

Creatinine (μmol/L)

1.01 (1.00, 1.01) **

1.00 1.00, 1.01)

1.01 (1.00, 1.01) **

1.00 (0.99, 1.00)

BMI (kg/m²)

0.98 (0.96, 1.00)

0.97 (0.95, 1.00)

0.95 (0.92, 0.98) **

0.93 (0.90, 0.97) **

Systolic blood pressure (mmHg)

1.01(1.00,1.01) **

1.01(1.00,1.02) **

1.01(0.99,1.01)

1.01(1.005,1.02) **

HbA1c (per %)

1.32(1.24,1.39) **

1.26 (1.19,1.33) **

1.33(1.24,1.42) **

1.26 (1.18, 1.35) **

Gender, rural vs urban residency, smoking, alcohol consumption, family history of DM, and level of education were all unassociated with risk of any DR or of STDR in multivariate logistic models.

Burden Of Blindness And Visual Impairment:

Among all participants, there were 382 (14.3%) persons (598 eyes, 11.2%) with at least one eye having VI, 53 (2.0%) people (71 eyes, 1.3%) with SVI and 182 (6.8%) people (208 eyes 3.9%) with at least one eye blind.

Although half of the PwDM in our study had DM for < 5 years, our findings of 31.1% DR prevalence are comparable to recent studies in both Hong Kong and the UK through clinic based screening, with prevalence of 39.0% (95% CI: 38.8–39.2), and 33.8% respectively, where PwDM had much longer duration of DM^18,19. This suggests that the actual duration of DM prior to diagnosis may have been longer in our cohort in the present study, which is consistent with prior studies showing a low rate of prior diagnosis (14%) among PwDM in this setting²⁰. An alternative explanation for the relatively high prevalence of DR after a brief apparent period of exposure to DM may be control of glucose and other DR risk factors: nearly three-quarters (71.0%) of participants in the current study had HbA1c > 6.5% and two-thirds (66.2%) had uncontrolled hypertension. Rates of poor glucose control were especially high among urban dwellers. This evidence of poor management of common non-communicable diseases, resulting in a comparatively high prevalence of end-organ damage such as DR, has important implications for health policy makers in China.

Prevalence of blindness and visual impairment among these PwDM aged over 18 years in Qujiang was lower than that among other population-based studies for people over 50 years²¹ and higher than that for all age groups²² in China.

Other clinic-based studies in China examining DR prevalence among PwDM registered in clinics at different levels have reported rates from 18.0% (year 2015 in urban Suzhou, 95% CI: 15.5–20.6)³ to 27.9% (8 hospitals across China in 2016–2016, 95% CI: 27.2–28.6)⁹ to 32.8% (Dongguan City in Guangdong Province between 2011 and 2012)²³. None of these studies, however, followed our gold standard approach of assessing photographic images using experienced graders, and direct examination of the retina in clinic may have led to under-estimation of DR, as has been reported in China²⁴.

Rural-dwellers in the current study were less-educated and more likely to smoke and drink regularly than urban-dwellers. Nonetheless, we found no difference in DR prevalence by urban vs rural residence. In adjusting for age (younger in rural dwellers) and duration of diabetes (shorter in rural dwellers) there was still no significant difference detected in DR prevalence.

Our findings that elevated blood pressure and poorly controlled blood glucose were associated with higher rates of DR are consistent with large trials of glucose and blood pressure control, which have consistently shown lower rates of end-organ diabetic damage such as DR^25,26. The observed linear association between duration of DM and DR prevalence is also a common feature of DM, particularly in this setting, where glucose and blood pressure control are poor, as noted above. While men were at greater risk of any DR and STDR than women in the univariate regression, this association was no longer significant when adjusting for other clinical and demographic factors

Our finding that persons under current treatment with insulin/hypoglycemic agents and those having had recent retinal examinations were at greater risk for DR likely reflects the fact that those with more severe disease, resulting in worse DR, were more likely to be receiving aggressive treatment, and to have visual symptoms, leading to greater uptake of ocular examinations. The apparent decline in DR with older age (despite the fact that DR increased with duration of DM), likely reflects a similar phenomenon: those surviving to an older age with DM likely have less severe disease, with a later onset, and are thus at lower risk for end-organ damage such as DR.

Though this study was not population-based, and thus cannot be taken as representative of PwDM in this southern Chinese setting, it does provide important information on the quality of DM care in China, which has previously been lacking for rural hospitals. Other strengths include the large size, relatively high uptake of offered vision examinations, our ability to compare participants with non-participants using existing health records and our use of photographic images and experienced graders to determine the prevalence of DR. The latter has not been done before in studies of diabetes management in rural China. Limitations must also be addressed: though participation in the offered eye examinations was relatively high at approximately three-quarters of those eligible, persons who presented differed from those who did not, having both younger age and worse-controlled blood pressure. While data were collected at ten township health units, all of these facilities were in the same region of Guangdong Province, southern China, and extrapolation to other regions can only be made with care.

Despite its limitations, our study was among the very few to assess management of DM at the facility level in rural China by examining DR as an index of end-organ damage using state-of the-art image grading techniques. Our finding of high DR prevalence despite a relatively brief exposure to DM, together with high rates of poor glucose and BP control, deliver an important message to healthcare policy makers in China on the need to improve management of non-communicable disease in hospital settings.

Ethical approval and consent to participate:

Ethical approval for this study was obtained from the Ethics Committee of Zhongshan Ophthalmic Center, Sun Yat-sen University, on 30 May 2019 (reference No.2019KYPJ067). Written informed consent was obtained for all the participants, for literates or fingerprint informed consent for illiterates was obtained from all participants. Taking fingerprint informed consent for illiterates was approved by the Ethics Committee of Zhongshan Ophthalmic Center, Sun Yat-sen University.

PwDM found with DR at the pre-proliferative stage or beyond, any maculopathy, operable cataract or other diagnosed or suspected eye diseases were referred to Shaoguan Hospital for further examination and treatment as needed. The study fulfilled the tenets of the Declaration of Helsinki.

Consent for publication: Not applicable.

Availability of Data and Materials (ADM): The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing interests: The authors declare that they have no competing interests.

Funding: The study was financially supported by: The World Diabetes Foundation, Orbis International. Prof Nathan Congdon is funded by MRC (R1087CPH) and Wellcome (R2806CPH). Ping Xu and Jia Li work for Orbis International.

Authors’ contributions:

Baixiang Xiao designed and monitored the whole study, analyzed data, initially drafted and revised the manuscript.

Fang Duan contributed to initial draft of the manuscript.

Jiahao Zuo, Xiaojun Zhou and Ling Jin analyzed data.

Xuejun Gu, Ving Fai Chan, Gianni Virgili, Yanfang Wang, Yun He, Dongfeng Li, Ping Xu, Jia Li and Wenyong Huang critically commented and revised the manuscript.

Carlos Price-Sanchez corrected English and critically commented on the manuscript.

Yanfang Wang, Yichun Zhong, Qinghua Liao, Haoxiang Fu coordinated data collection and commented critically on the manuscript.

Nathan Congdon guided the study generally and critically revised the manuscript.

Acknowledgement:

The authors acknowledge Ms Qiong Wan, the head of the screening team, doctors and nurses from Zhenjiang District hospital and the 10 township health units in Qujiang district, Shaoguan City, for their contribution to the screening and data collection.

IDF. International Diabetes Federation Diabetes Altas -. English Edition – 2017 http://wwwdiabetesatlas.org/resources/2017-atlas.html. Accessed 8th April 2020.
Ogurtsova K, da Rocha Fernandes JD, Huang Y, et al. IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017;128:40–50.
Pan CW, Wang S, Qian DJ, Xu C, Song E. Prevalence, Awareness, and Risk Factors of Diabetic Retinopathy among Adults with Known Type 2 Diabetes Mellitus in an Urban Community in China. Ophthalmic Epidemiol. 2017;24(3):188–94.
2018). ADAM. Economic costs of diabetes in the U.S. in 2017. Diabetes Care; 41 (5): 917–28.
Yang SH, Dou KF, Song WJ. Prevalence of diabetes among men and women in China. N Engl J Med. 2010;362(25):2425–6.
Ferris FL. 3rd. Results of 20 years of research on the treatment of diabetic retinopathy. Prev Med. 1994;23(5):740–2.
Harris M, The, NHS Diabetic Eye Screening Programme. : New Common Pathway https:i>//wwwrcophthacuk/wp-content/uploads/2014/08/Focus-Winter-2012pdf Accessed March 8th 2022.
Song P, Yu J, Chan KY, Theodoratou E, Rudan I. Prevalence, risk factors and burden of diabetic retinopathy in China: a systematic review and meta-analysis. J Glob Health. 2018;8(1):010803.
Zhang G, Chen H, Chen W, Zhang M. Prevalence and risk factors for diabetic retinopathy in China: a multi-hospital-based cross-sectional study. Br J Ophthalmol. 2017;101(12):1591–5.
Liu Y, Yang J, Tao L, et al. Risk factors of diabetic retinopathy and sight-threatening diabetic retinopathy: a cross-sectional study of 13 473 patients with type 2 diabetes mellitus in mainland China. BMJ Open. 2017;7(9):e016280.
Jin G, Xiao W, Ding X, et al. Prevalence of and Risk Factors for Diabetic Retinopathy in a Rural Chinese Population: The Yangxi Eye Study. Invest Ophthalmol Vis Sci. 2018;59(12):5067–73.
Wang D, Ding X, He M, et al. Use of eye care services among diabetic patients in urban and rural China. Ophthalmology. 2010;117(9):1755–62.
Wang FH, Liang YB, Zhang F, et al. Prevalence of diabetic retinopathy in rural China: the Handan Eye Study. Ophthalmology. 2009;116(3):461–7.
Xie XW, Xu L, Jonas JB, Wang YX. Prevalence of diabetic retinopathy among subjects with known diabetes in China: the Beijing Eye Study. Eur J Ophthalmol. 2009;19(1):91–9.
Xu J, Wei WB, Yuan MX, et al. Prevalence and risk factors for diabetic retinopathy: the Beijing Communities Diabetes Study 6. Retina. 2012;32(2):322–9.
Cui J, Ren JP, Chen DN, et al. Prevalence and associated factors of diabetic retinopathy in Beijing, China: a cross-sectional study. BMJ Open. 2017;7(8):e015473.
Zhang L, Cui H, Zhao J, et al. [Prevalence of blindness and moderate and severe visual impairment among adults aged 50 years or above in Shuangcheng City of Heilongjiang Province: the China Nine-Province Survey]. Zhonghua Yan Ke Za Zhi. 2014;50(3):173–8.
Lian JX, Gangwani RA, McGhee SM, et al. Systematic screening for diabetic retinopathy (DR) in Hong Kong: prevalence of DR and visual impairment among diabetic population. Br J Ophthalmol. 2016;100(2):151–5.
Haider S, Thayakaran R, Subramanian A, et al. Disease burden of diabetes, diabetic retinopathy and their future projections in the UK: cross-sectional analyses of a primary care database. BMJ Open. 2021;11(7):e050058.
Jin G, Ding X, Xiao W, et al. Prevalence of age-related macular degeneration in rural southern China: the Yangxi Eye Study. Br J Ophthalmol. 2018;102(5):625–30.
He Y, Nie A, Pei J, et al. Prevalence and causes of visual impairment in population more than 50 years old: The Shaanxi Eye Study. Med (Baltim). 2020;99(20):e20109.
Xu T, Wang B, Liu H, et al. Prevalence and causes of vision loss in China from 1990 to 2019: findings from the Global Burden of Disease Study 2019. Lancet Public Health. 2020;5(12):e682–e91.
Cui Y, Zhang M, Zhang L, et al. Prevalence and risk factors for diabetic retinopathy in a cross-sectional population-based study from rural southern China: Dongguan Eye Study. BMJ Open. 2019;9(9):e023586.
McKenna M, Chen T, McAneney H, et al. Accuracy of trained rural ophthalmologists versus non-medical image graders in the diagnosis of diabetic retinopathy in rural China. Br J Ophthalmol. 2018;102(11):1471–6.
Tight blood pressure control. and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. UK Prospective Diabetes Study Group. BMJ. 1998;317(7160):703–13.
Intensive blood-glucose. control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998;352(9131):837–53.

No competing interests reported.

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Differences of prevalence and risk factors of diabetic retinopathy among rural and urban residents in South China

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Abstract

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Introduction

Methods

Patient and public involvement statement:

Data Collection

Biochemical Detection

Image Grading And Definition Of Visual Acuity:

Statistical Methods:

Results

Characteristics of participants:

Prevalence Of Dr And Macular Edema:

Burden Of Blindness And Visual Impairment:

Discussion

Declarations

References

Additional Declarations

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